Advances in Supply Chain Resilience: Predictive Models for Vendor Risk Assessment and Procurement Cost Optimization
Abstract
Supply chain disruptions between 2018 and 2022 imposed material losses on firms that lacked the capacity to anticipate supplier failure and to contain its cost consequences, yet the field still lacks an integrated account of how predictive analytics reshaped two functions that were historically managed in isolation: vendor risk assessment and procurement cost optimization. This advances review traces the evolution of these intertwined domains from the early conceptual treatments of supply chain resilience through the contemporary state of the art in machine learning, simulation, and digital twin methods, synthesizing more than one hundred studies published between 1991 and 2024. Three consistent patterns emerge from the evidence. First, the analytical center of gravity moved from reactive, post-disruption recovery toward forward-looking prediction, with data- driven supplier disruption models reporting earlier warning and measurable reductions in exposure relative to static scoring approaches. Second, vendor risk and cost optimization, long treated as competing objectives, increasingly converge within unified decision architectures that price resilience explicitly rather than treating it as an unbudgeted contingency. Third, the dominant theoretical lenses shifted from a single resource-based reading toward a pluralist synthesis that combines dynamic capabilities, the relational view, and complexity thinking. These patterns suggest that resilience is no longer a discretionary overlay on procurement but a measurable property of the sourcing portfolio that can be designed, priced, and continuously monitored, with direct implications for procurement leaders, risk officers, and operations scholars. The review also documents persistent disagreement over whether redundancy or flexibility delivers superior protection per unit of cost, and over the external validity of conceptual frameworks that remain weakly tested in field settings. The field now understands resilience and efficiency as jointly optimizable rather than mutually exclusive, reframing the central procurement question from how much protection a firm can afford toward how precisely it can target protection where disruption risk and cost both concentrates.
Keywords
predictive analytics; supplier disruption; sourcing portfolio; resilience capability; total cost of ownership; disruption recovery; supply risk modeling; operations management.
References
Akinleye, O. K., & Adeyoyin, O. (2021). Process automation framework for enhancing procurement efficiency and transparency. Shodhshauryam, International Scientific Refereed Research Journal, 4(4), 356-387. Akinleye, O. K., & Adeyoyin, O. (2022a). A negotiation optimization model for reducing procurement costs in manufacturing firms. Shodhshauryam, International Scientific Refereed Research Journal, 5(5), 398-435. Akinleye, O. K., & Adeyoyin, O. (2022b). Supplier relationship management framework for achieving strategic procurement objectives. Gyanshauryam, International Scientific Refereed Research Journal, 5(4), 565-598. Efobi, O. Z., Akinleye, O. K., & Fasawe, O. (2021). Framework for data-driven operations management and performance improvement in educational institutions. Gyanshauryam, International Scientific Refereed Research Journal, 4(6), 127-158. Efobi, O. Z., Akinleye, O. K., & Fasawe, O. (2022a). Conceptual framework for sustainable procurement practices in local manufacturing enterprises in Africa. Gyanshauryam, International Scientific Refereed Research Journal, 5(6), 248-266. Efobi, O. Z., Akinleye, O. K., & Fasawe, O. (2022b). Conceptual model for data-driven lean supply chain optimization in manufacturing and retail operations. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 8(2), 703-734. Efobi, O. Z., Akinleye, O. K., & Fasawe, O. (2023). Conceptual framework for developing a resilience index for post-pandemic supply chains. Shodhshauryam, International Scientific Refereed Research Journal, 6(2), 421-432. Akinleye, O. K., Okoruwa, P. O., Babatope, O. M., & Akokodaripon, D. A. (2023). Leveraging big data and business intelligence for optimization of manufacturing sector procurement. International Journal of Advanced Multidisciplinary Research and Studies, 3(6), 2164- 2172. Akin-Oluyomi, O. T., Atima, M. E., Akinleye, O. K., & Okoruwa, P. O. (2023a). Predictive analytics approaches for improving demand forecasting accuracy in e-commerce procurement systems. International Journal of Advanced Multidisciplinary Research and Studies, 3(6), 2173-2182. Akin-Oluyomi, O. T., Atima, M. E., & Akinleye, O. K. (2023b). Green procurement strategies for balancing cost efficiency with long-term environmental responsibility. International Journal of Advanced Multidisciplinary Research and Studies, 3(6), 2183-2193. Akin-Oluyomi, O. T., Atima, M. E., & Akinleye, O. K. (2023c). Regulatory compliance and supplier risk assessment frameworks in international pharmaceutical procurement. International Journal of Advanced Multidisciplinary Research and Studies, 3(6), 2194- 2204. Babatope, O. M., Akokodaripon, D. A., Akinleye, O. K., & Okoruwa, P. O. (2023). The role of data visualization in enhancing strategic procurement decision-making effectiveness. International Journal of Advanced Multidisciplinary Research and Studies, 3(6), 2205- 2212. Akin-Oluyomi, O. T., Okoruwa, P. O., Babatope, O. M., & Akokodaripon, D. A. (2023d). Evaluating supplier sustainability metrics through data-driven procurement and supply chain frameworks. International Journal of Advanced Multidisciplinary Research and Studies, 3(6), 2213-2223. Akin-Oluyomi, O. T., Atima, M. E., Akinleye, O. K., & Akokodaripon, D. A. (2020). Using Tableau and Excel for comprehensive profitability analysis in retail procurement operations. International Journal of Multidisciplinary Research and Growth Evaluation, 1(5), 385-393. Akin-Oluyomi, O. T., Atima, M. E., & Akinleye, O. K. (2024). Cross-border supplier relationship management frameworks for pharmaceutical and global construction sectors. International Journal of Multidisciplinary Research and Growth Evaluation, 5(6), 1709-1718. Okoruwa, P. O., Babatope, O. M., Akokodaripon, D. A., & Akinleye, O. K. (2024). Developing integrated digital platforms for enhancing transparency in procurement and supply chain management. International Journal of Multidisciplinary Research and Growth Evaluation, 5(6), 1719-1729. Akokodaripon, D. A., Akinleye, O. K., Okoruwa, P. O., & Babatope, O. M. (2023). Procurement cost optimization strategies: Comparative analyses across UK, Nigeria, and emerging economies. International Journal of Advanced Multidisciplinary Research and Studies, 3(6), 2224-2234. Akinleye, O. K. (2024). A sustainable procurement and resilience framework for post-pandemic pharmaceutical operations. International Journal of Advanced Multidisciplinary Research and Studies, 4(1), 1602-1621. Akinleye, O. K. (2023). Framework for quantitative evaluation of ESG adoption within SME supply chains in emerging economies. International Journal of Advanced Multidisciplinary Research and Studies, 3(6), 2317-2334. Okonkwo, C. S., Ogunwole, O., & Okeke, O. T. (2018a). Framework for strategic procurement optimization in oil and gas operations. IRE Journals, 1(7), 153-168. Okonkwo, C. S., Ogunwole, O., & Okeke, O. T. (2018b). Model for inventory availability and plant uptime improvement in energy facilities. Iconic Research and Engineering Journals, 2(4), 160-172. Ogunwole, O., Okonkwo, C. S., Agbabiaka, J., Mayo, W., & Okeke, O. T. (2021). Supply chain resilience framework for critical infrastructure and gas processing plants. Shodhshauryam, International Scientific Refereed Research Journal, 4(4), 444-461. Okonkwo, C. S., Agbabiaka, J., Ogunwole, O., Mayo, W., & Okeke, O. T. (2021). Conceptual model for materials readiness and maintenance-driven supply chain performance. International Journal of Multidisciplinary Research and Growth Evaluation, 2(6), 584- 594. Agbabiaka, J., Okonkwo, C. S., Ogunwole, O., Mayo, W., & Okeke, O. T. (2019). Supply chain risk management model for EPC and gas processing projects. IRE Journals, 3(2), 968-980. Okonkwo, C. S., Ogunwole, O., Okeke, O. T., & Mayo, W. (2019). Conceptual framework for cost reduction through contract negotiation and vendor governance. IRE Journals, 2(9), 468-482. Patrick, M. C. A., Okonkwo, C. S., Mayo, W., & Okeke, O. T. (2021). Model for data driven vendor evaluation and bid selection using geospatial intelligence. Shodhshauryam, International Scientific Refereed Research Journal, 4(4), 426-443. Patrick, M. C. A., Okonkwo, C. S., Mayo, W., & Okeke, O. T. (2020). A GIS enabled framework for modern ERP procurement processes. International Journal of Multidisciplinary Research and Growth Evaluation, 1(5), 499-508. Okonkwo, C. S., Agbabiaka, J., Mayo, W., & Okeke, O. T. (2024a). Model for predictive procurement planning to sustain operational uptime. International Journal of Scientific Research in Humanities and Social Sciences, 1(2), 909-928. Okonkwo, C. S., Agbabiaka, J., Mayo, W., & Okeke, O. T. (2024b). Conceptual framework for digital supply chain governance in energy and infrastructure sectors. Gyanshauryam, International Scientific Refereed Research Journal, 7(4), 335-356. Okonkwo, C. S., Mayo, W., & Okeke, O. T. (2023). Conceptual model for asset lifecycle management and inventory visibility. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 10(1), 809-824. Okonkwo, C. S., Patrick, M. C. A., Okeke, O. T., & Mayo, W. (2023). Framework for integrating IT systems engineering with supply chain operations. International Journal of Advanced Multidisciplinary Research and Studies, 3(6), 2580-2589. Okonkwo, C. S., Agbabiaka, J., Mayo, W., & Okeke, O. T. (2024c). Framework for secure and scalable supply chain systems supporting national energy reliability. International Journal of Advanced Multidisciplinary Research and Studies, 4(6), 2816-2826. Okonkwo, C. S., Agbabiaka, J., Mayo, W., & Okeke, O. T. (2024d). Review of digital supply chain models for cost control and operational continuity. International Journal of Advanced Multidisciplinary Research and Studies, 4(6), 2836-2846. Okonkwo, C. S., Agbabiaka, J., Mayo, W., & Okeke, O. T. (2024e). Review of advances in procurement strategy, ERP adoption, and logistics performance. International Journal of Advanced Multidisciplinary Research and Studies, 4(6), 2827-2835. Okonkwo, C. S., Agbabiaka, J., Mayo, W., & Okeke, O. T. (2024f). Supply chain automation framework using service management platforms. Shodhshauryam, International Scientific Refereed Research Journal, 7(2), 157-177. Okonkwo, C. S., Ogunwole, O., Mayo, W., & Okeke, O. T. (2021). Framework for regulatory- compliant procurement in high-risk energy environments. International Journal of Multidisciplinary Research and Growth Evaluation, 2(6), 595-605. Okonkwo, C. S., Agbabiaka, J., Ogunwole, O., Mayo, W., & Okeke, O. T. (2020). Model for demurrage elimination and port logistics efficiency in emerging economies. International Journal of Multidisciplinary Research and Growth Evaluation, 1(5), 552-562. Aifuwa, S. E., Oshoba, T. O., Ogbuefi, E., Ike, P. N., Nnabueze, S. B., & Olatunde-Thorpe, J. (2020). Predictive analytics models enhancing supply chain demand forecasting accuracy and reducing inventory management inefficiencies. International Journal of Multidisciplinary Research and Growth Evaluation, 1(3), 171-181. Filani, O. M., Nnabueze, S. B., Ike, P. N., & Wedraogo, L. (2022). Real-time risk assessment dashboards using machine learning in hospital supply chain management systems. International Journal of Multidisciplinary Evolutionary Research, 3(1), 65-76. Ike, P. N., Ogbuefi, E., Nnabueze, S. B., Olatunde-Thorpe, J., Aifuwa, S. E., Oshoba, T. O., & Akokodaripon, D. (2021). Supplier relationship management strategies fostering innovation, collaboration, and resilience in global supply chain ecosystems. International Journal of Multidisciplinary Evolutionary Research, 2(2), 52-62. Ike, P. N., Ogbuefi, E., Nnabueze, S. B., Olatunde-Thorpe, J., Aifuwa, S. E., Oshoba, T. O., & Akokodaripon, D. (2022). Lean supply chain practices improving operational efficiency, reducing waste, and enhancing organizational competitiveness globally. Journal of Frontiers in Multidisciplinary Research, 3(2), 182-192. Nnabueze, S. B., Ike, P. N., Olatunde-Thorpe, J., Aifuwa, S. E., Oshoba, T. O., Ogbuefi, E., & Akokodaripon, D. (2021). End-to-end visibility frameworks improving transparency, compliance, and traceability across complex global supply chain operations. International Journal of Multidisciplinary Futuristic Development, 2(2), 50-60. Ike, P. N., Aifuwa, S. E., Nnabueze, S. B., Olatunde-Thorpe, J., Ogbuefi, E., Oshoba, T. O., & Akokodaripon, D. (2024b). Quantitative risk architecture for public-private partnerships: A multi-layered model for allocating public and private risk. International Journal of Advanced Multidisciplinary Research and Studies, 4(6), 2669-2682. Okojie, J. S., Filani, O. M., Ike, P. N., Okojokwu-Idu, J. O., Nnabueze, S. B., & Ihwughwavwe, S. I. (2023). Integrating AI with ESG metrics in smart infrastructure auditing for high-impact urban development projects. International Journal of Multidisciplinary Futuristic Development, 4(1), 32-44. Okojie, J., Ike, P., Idu, J., Nnabueze, S. B., Filani, O., & Ihwughwavwe, S. (2023). Predictive analytics models for monitoring smart city emissions and infrastructure risk in urban ESG planning. International Journal of Multidisciplinary Futuristic Development, 4(1), 45-57. Okojie, J. S., Filani, O. M., Ihwughwavwe, S. I., & Sakyi, J. K. (2020). Sustainable procurement practices: ESG-integrated supply chain models for corporate responsibility and environmental performance. IRE Journals, 4(2), 1-20. Lawal, O. A., & Oduleye, T. E. (2019a). A conceptual risk assessment model for transfer pricing in multinational corporations. IRE Journals, 2(12), 1-15. Lawal, O. A., & Oduleye, T. E. (2019b). Conceptualizing data driven executive decision systems for strategic financial planning. IRE Journals, 3(3), 1-14. Lawal, O. A., & Oduleye, T. E. (2018a). A conceptual model for financial analytics driven enterprise value creation in technology firms. IRE Journals, 2(2), 1-13. Lawal, O. A., & Oduleye, T. E. (2018b). A review and conceptual framework for tax governance and cross-border compliance analytics. IRE Journals, 2(5), 1-16. Lawal, O. A., & Oduleye, T. E. (2021a). A conceptual decision model for capital allocation using financial analytics. Gyanshauryam, International Scientific Refereed Research Journal, 4(2), 269-295. Lawal, O. A., & Oduleye, T. E. (2021b). Aligning financial planning analytics with corporate strategy: A conceptual integration model. Shodhshauryam, International Scientific Refereed Research Journal, 4(3), 319-346. Lawal, O. A., & Oduleye, T. E. (2023). Behavioral financial analytics: A conceptual model for explaining enterprise performance. International Journal of Advanced Multidisciplinary Research and Studies, 3(6), 2590-2604. Oduleye, T. E., & Medon, J. J. (2023a). A predictive model for optimizing cash flow and working capital management in corporations. Gyanshauryam, International Scientific Refereed Research Journal, 6(5), 739-754. Oduleye, T. E., & Medon, J. J. (2023b). A quantitative model for measuring the strategic impact of financial analysis on enterprise growth. International Journal of Advanced Multidisciplinary Research and Studies, 3(1), 1663-1672. Medon, J. J., & Oduleye, T. E. (2022). A comprehensive financial reporting model for strengthening compliance and organizational accountability systems. International Journal of Multidisciplinary Research and Growth Evaluation, 3(6), 768-777. Medon, J. J., & Oduleye, T. E. (2024). An integrated predictive analytics model for enhancing strategic financial forecasting and decision accuracy. Gyanshauryam, International Scientific Refereed Research Journal, 7(3), 258-279. Oduleye, T. E., & Medon, J. J. (2021). A data-driven cost management model for improving strategic financial planning and performance evaluation. International Journal of Multidisciplinary Research and Growth Evaluation, 2(6), 524-537. Adesuyi, M. O., Walawalkar, G., & Kalu, A. (2022). Predictive budgeting models using operational and market signals. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 8(5), 818-837. Adesuyi, M. O., Kalu, A., & Walawalkar, G. (2023). Data-led cost governance in technology- intensive enterprises. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 9(3), 877-896. Aliliele, C., Eboh, E. E., & Oluwo, K. (2024). Advances in variance analytics for cost control in manufacturing and industrial enterprises. International Journal of Advanced Multidisciplinary Research and Studies, 4(6), 3163-3185. Dosunmu, A. A., & Ogundele, P. O. (2019). Security audit and enterprise risk assessment frameworks for resilient information systems. IRE Journals, 3(5), 1-18. Dosunmu, A. A., & Ogundele, P. O. (2024). Cyber risk quantification models for prioritizing enterprise security investment decisions. International Journal of Multidisciplinary Research and Growth Evaluation, 5(6), 1777-1785. Akeju, B., Edivri, J., Ogbole, J. I., Okoruwa, P. O., Fadayomi, O., & Abolaji, T. O. (2018). Conceptual model for insider threat classification and risk modeling in complex digital systems. Iconic Research and Engineering Journals, 1(9), 476-492. Fadayomi, O., Abolaji, T. O., Edivri, J., Ogbole, J. I., Okoruwa, P. O., & Akeju, B. (2019). Risk- based cybersecurity assurance and data availability: Limitations, advances and future research opportunities. Iconic Research and Engineering Journals, 2(12), 602-617. Mbonu, I. S., Aliliele, C., Iwuanyanwu, U., & Oluoha, O. M. (2018). A conceptual framework for legal and ethical risk modeling in enterprise data protection governance systems. Iconic Research and Engineering Journals, 2(2), 207-226. Aliliele, C., Mbonu, I. S., & Iwuanyanwu, U. (2023). A review of API governance and risk prioritization frameworks in modern financial institutions. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 9(10), 395-433. Mbonu, I. S., Aliliele, C., Iwuanyanwu, U., & Uzoka, E. (2021). A conceptual framework for risk based business intelligence architecture in financial technology platforms. International Journal of Multidisciplinary Research and Growth Evaluation, 2(6), 731-746. Annan, A. O. (2022). Data privacy governance models for cross-border digital platforms. International Journal of Multidisciplinary Research and Growth Evaluation, 3(6), 949- 964. Kumuyi, O., Akeju, B., Uzoka, E., & Ozowara, D. E. (2023). Framework for blockchain-based cross-border data exchange and regulatory transparency. International Journal of Multidisciplinary Futuristic Development, 4(1), 99-113. Sunday, E. A., Omoegun, G. O., Essien, M. A., & Oluokun, O. A. (2020). Transitioning from reactive to predictive maintenance in mechanical systems. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 6(6), 425-447. Mayo, W., Ogbole, J. I., Okoruwa, P. O., & Babatope, O. M. (2021). Designing an AI-predictive maintenance model for e-commerce systems using machine learning and cloud analytics. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 7(5), 416-440. Akanbi, O., & Sunday, E. A. (2024). An integrated path-planning and slotting optimization model for AMR-enabled high-density warehousing. International Journal of Advanced Multidisciplinary Research and Studies, 4(6), 3226-3243. Anene, U. N., & Clement, T. (2022). A resilient logistics framework for humanitarian supply chains: Integrating predictive analytics, IoT, and localized distribution to strengthen emergency response systems. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 8(5), 398-424. Anene, U. N., & Clement, T. (2024). Localized supply chain solutions for sustainable community development: A strategic model for economic revitalization and regional resilience. International Journal of Scientific Research in Science and Technology, 11(5), 736-776. Akinlade, O. F., Filani, O. M., & Nwachukwu, P. S. (2024). Automation and digital twins framework reducing procurement errors and turnaround time. International Journal of Scientific Research in Humanities and Social Sciences, 1(1), 197-216. Ekwunife, D. I., Precious, O. T., Rasul, O. A., Akinlade, O. F., Nwokoro, T. O., & Ikpe, V. I. (2024). Using blockchain technology to maximize supply chain and logistics management in North America. International Journal of Science and Research Archive, 12(2), 854-863. Rukh, S., Seyi-Lande, O. B., & Oziri, S. T. (2024). An integrated framework for AI and predictive analytics in supply chain management. International Journal of Scientific Research in Humanities and Social Sciences, 1(1), 451-491. Akinola, A. S., Adesanya, O. S., Okafor, C. M., & Dako, O. F. (2024). Value-chain automation in beverage logistics: Throughput, capacity, and cost avoidance via queueing models. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 10(4), 1112-1132. Edivri, J., & Oteri, O. (2022). Predictive capacity planning and resource utilization forecasting models for multi-program and multi-stakeholder IT portfolios. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 8(4), 826-845. Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99-120. Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509-533. Pfeffer, J., & Salancik, G. R. (1978). The external control of organizations: A resource dependence perspective. Harper & Row. DiMaggio, P. J., & Powell, W. W. (1983). The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. American Sociological Review, 48(2), 147- 160. Williamson, O. E. (2008). Outsourcing: Transaction cost economics and supply chain management. Journal of Supply Chain Management, 44(2), 5-16. Ellram, L. M. (1995). Total cost of ownership: An analysis approach for purchasing. International Journal of Physical Distribution & Logistics Management, 25(8), 4-23. Lee, H. L., Padmanabhan, V., & Whang, S. (1997). Information distortion in a supply chain: The bullwhip effect. Management Science, 43(4), 546-558. Fisher, M. L. (1997). What is the right supply chain for your product? Harvard Business Review, 75(2), 105-116. Swaminathan, J. M., Smith, S. F., & Sadeh, N. M. (1998). Modeling supply chain dynamics: A multiagent approach. Decision Sciences, 29(3), 607-632. Cachon, G. P., & Fisher, M. (2000). Supply chain inventory management and the value of shared information. Management Science, 46(8), 1032-1048. de Boer, L., Labro, E., & Morlacchi, P. (2001). A review of methods supporting supplier selection. European Journal of Purchasing & Supply Management, 7(2), 75-89. Sarkis, J., & Talluri, S. (2002). A model for strategic supplier selection. Journal of Supply Chain Management, 38(1), 18-28. Zsidisin, G. A., & Ellram, L. M. (2003). An agency theory investigation of supply risk management. Journal of Supply Chain Management, 39(2), 15-27. Hendricks, K. B., & Singhal, V. R. (2003). The effect of supply chain glitches on shareholder wealth. Journal of Operations Management, 21(5), 501-522. Chopra, S., & Sodhi, M. S. (2004). Managing risk to avoid supply-chain breakdown. MIT Sloan Management Review, 46(1), 53-61. Christopher, M., & Peck, H. (2004). Building the resilient supply chain. The International Journal of Logistics Management, 15(2), 1-14. Hallikas, J., Karvonen, I., Pulkkinen, U., Virolainen, V. M., & Tuominen, M. (2004). Risk management processes in supplier networks. International Journal of Production Economics, 90(1), 47-58. Lee, H. L. (2004). The triple-A supply chain. Harvard Business Review, 82(10), 102-112. Zsidisin, G. A., Ellram, L. M., Carter, J. R., & Cavinato, J. L. (2004). An analysis of supply risk assessment techniques. International Journal of Physical Distribution & Logistics Management, 34(5), 397-413. Hendricks, K. B., & Singhal, V. R. (2005). An empirical analysis of the effect of supply chain disruptions on long-run stock price performance and equity risk of the firm. Production and Operations Management, 14(1), 35-52. Kleindorfer, P. R., & Saad, G. H. (2005). Managing disruption risks in supply chains. Production and Operations Management, 14(1), 53-68. Sheffi, Y., & Rice, J. B. (2005). A supply chain view of the resilient enterprise. MIT Sloan Management Review, 47(1), 41-48. Choi, T. Y., & Krause, D. R. (2006). The supply base and its complexity: Implications for transaction costs, risks, responsiveness, and innovation. Journal of Operations Management, 24(5), 637-652. Tang, C. S. (2006). Perspectives in supply chain risk management. International Journal of Production Economics, 103(2), 451-488. Tomlin, B. (2006). On the value of mitigation and contingency strategies for managing supply chain disruption risks. Management Science, 52(5), 639-657. Wu, T., Blackhurst, J., & Chidambaram, V. (2006). A model for inbound supply risk analysis. Computers in Industry, 57(4), 350-365. Cohen, M. A., & Kunreuther, H. (2007). Operations risk management: Overview of Paul Kleindorfer's contributions. Production and Operations Management, 16(5), 525-541. Craighead, C. W., Blackhurst, J., Rungtusanatham, M. J., & Handfield, R. B. (2007). The severity of supply chain disruptions: Design characteristics and mitigation capabilities. Decision Sciences, 38(1), 131-156. Carbonneau, R., Laframboise, K., & Vahidov, R. (2008). Application of machine learning techniques for supply chain demand forecasting. European Journal of Operational Research, 184(3), 1140-1154. Manuj, I., & Mentzer, J. T. (2008). Global supply chain risk management strategies. International Journal of Physical Distribution & Logistics Management, 38(3), 192-223. Tang, C., & Tomlin, B. (2008). The power of flexibility for mitigating supply chain risks. International Journal of Production Economics, 116(1), 12-27. Wagner, S. M., & Bode, C. (2008). An empirical examination of supply chain performance along several dimensions of risk. Journal of Business Logistics, 29(1), 307-325. Ponomarov, S. Y., & Holcomb, M. C. (2009). Understanding the concept of supply chain resilience. The International Journal of Logistics Management, 20(1), 124-143. Ho, W., Xu, X., & Dey, P. K. (2010). Multi-criteria decision making approaches for supplier evaluation and selection: A literature review. European Journal of Operational Research, 202(1), 16-24. Pettit, T. J., Fiksel, J., & Croxton, K. L. (2010). Ensuring supply chain resilience: Development of a conceptual framework. Journal of Business Logistics, 31(1), 1-21. Wagner, S. M., & Neshat, N. (2010). Assessing the vulnerability of supply chains using graph theory. International Journal of Production Economics, 126(1), 121-129. Blackhurst, J., Dunn, K. S., & Craighead, C. W. (2011). An empirically derived framework of global supply resiliency. Journal of Business Logistics, 32(4), 374-391. Bode, C., Wagner, S. M., Petersen, K. J., & Ellram, L. M. (2011). Understanding responses to supply chain disruptions: Insights from information processing and resource dependence perspectives. Academy of Management Journal, 54(4), 833-856. Juttner, U., & Maklan, S. (2011). Supply chain resilience in the global financial crisis: An empirical study. Supply Chain Management: An International Journal, 16(4), 246-259. Sodhi, M. S., Son, B. G., & Tang, C. S. (2012). Researchers' perspectives on supply chain risk management. Production and Operations Management, 21(1), 1-13. Chai, J., Liu, J. N., & Ngai, E. W. (2013). Application of decision-making techniques in supplier selection: A systematic review of literature. Expert Systems with Applications, 40(10), 3872-3885. Pettit, T. J., Croxton, K. L., & Fiksel, J. (2013). Ensuring supply chain resilience: Development and implementation of an assessment tool. Journal of Business Logistics, 34(1), 46-76. Sawik, T. (2013). Selection of resilient supply portfolio under disruption risks. Omega, 41(2), 259- 269. Waller, M. A., & Fawcett, S. E. (2013). Data science, predictive analytics, and big data: A revolution that will transform supply chain design and management. Journal of Business Logistics, 34(2), 77-84. Wieland, A., & Wallenburg, C. M. (2013). The influence of relational competencies on supply chain resilience: A relational view. International Journal of Physical Distribution & Logistics Management, 43(4), 300-320. Brandon-Jones, E., Squire, B., Autry, C. W., & Petersen, K. J. (2014). A contingent resource-based perspective of supply chain resilience and robustness. Journal of Supply Chain Management, 50(3), 55-73. Chopra, S., & Sodhi, M. S. (2014). Reducing the risk of supply chain disruptions. MIT Sloan Management Review, 55(3), 73-80. Ambulkar, S., Blackhurst, J., & Grawe, S. (2015). Firm's resilience to supply chain disruptions: Scale development and empirical examination. Journal of Operations Management, 33- 34, 111-122. Fahimnia, B., Tang, C. S., Davarzani, H., & Sarkis, J. (2015). Quantitative models for managing supply chain risk: A review. European Journal of Operational Research, 247(1), 1-15. Heckmann, I., Comes, T., & Nickel, S. (2015). A critical review on supply chain risk: Definition, measure and modeling. Omega, 52, 119-132. Ho, W., Zheng, T., Yildiz, H., & Talluri, S. (2015). Supply chain risk management: A literature review. International Journal of Production Research, 53(16), 5031-5069. Schoenherr, T., & Speier-Pero, C. (2015). Data science, predictive analytics, and big data in supply chain management: Current state and future potential. Journal of Business Logistics, 36(1), 120-132. Scholten, K., & Schilder, S. (2015). The role of collaboration in supply chain resilience. Supply Chain Management: An International Journal, 20(4), 471-484. Simchi-Levi, D., Schmidt, W., Wei, Y., Zhang, P. Y., Combs, K., Ge, Y., Gusikhin, O., Sanders, M., & Zhang, D. (2015). Identifying risks and mitigating disruptions in the automotive supply chain. Interfaces, 45(5), 375-390. Torabi, S. A., Baghersad, M., & Mansouri, S. A. (2015). Resilient supplier selection and order allocation under operational and disruption risks. Transportation Research Part E, 79, 22- 48. Tukamuhabwa, B. R., Stevenson, M., Busby, J., & Zorzini, M. (2015). Supply chain resilience: Definition, review and theoretical foundations for further study. International Journal of Production Research, 53(18), 5592-5623. Kamalahmadi, M., & Parast, M. M. (2016). A review of the literature on the principles of enterprise and supply chain resilience: Major findings and directions for future research. International Journal of Production Economics, 171, 116-133. Snyder, L. V., Atan, Z., Peng, P., Rong, Y., Schmitt, A. J., & Sinsoysal, B. (2016). OR/MS models for supply chain disruptions: A review. IIE Transactions, 48(2), 89-109. Syntetos, A. A., Babai, Z., Boylan, J. E., Kolassa, S., & Nikolopoulos, K. (2016). Supply chain forecasting: Theory, practice, their gap and the future. European Journal of Operational Research, 252(1), 1-26. Wang, G., Gunasekaran, A., Ngai, E. W., & Papadopoulos, T. (2016). Big data analytics in logistics and supply chain management: Certain investigations for research and applications. International Journal of Production Economics, 176, 98-110. Chowdhury, M. M. H., & Quaddus, M. (2017). Supply chain resilience: Conceptualization and scale development using dynamic capability theory. International Journal of Production Economics, 188, 185-204. Gunasekaran, A., Papadopoulos, T., Dubey, R., Wamba, S. F., Childe, S. J., Hazen, B., & Akter, S. (2017). Big data and predictive analytics for supply chain and organizational performance. Journal of Business Research, 70, 308-317. Ivanov, D., Dolgui, A., Sokolov, B., & Ivanova, M. (2017). Literature review on disruption recovery in the supply chain. International Journal of Production Research, 55(20), 6158- 6174. Linnenluecke, M. K. (2017). Resilience in business and management research: A review of influential publications and a research agenda. International Journal of Management Reviews, 19(1), 4-30. Buyukozkan, G., & Gocer, F. (2018). Digital supply chain: Literature review and a proposed framework for future research. Computers in Industry, 97, 157-177. Choi, T. M., Wallace, S. W., & Wang, Y. (2018). Big data analytics in operations management. Production and Operations Management, 27(10), 1868-1883. Dolgui, A., Ivanov, D., & Sokolov, B. (2018). Ripple effect in the supply chain: An analysis and recent literature. International Journal of Production Research, 56(1-2), 414-430. Nguyen, T., Zhou, L., Spiegler, V., Ieromonachou, P., & Lin, Y. (2018). Big data analytics in supply chain management: A state-of-the-art literature review. Computers & Operations Research, 98, 254-264. Pavlov, A., Ivanov, D., Dolgui, A., & Sokolov, B. (2018). Hybrid fuzzy-probabilistic approach to supply chain resilience assessment. IEEE Transactions on Engineering Management, 65(2), 303-315. Baryannis, G., Validi, S., Dani, S., & Antoniou, G. (2019). Supply chain risk management and artificial intelligence: State of the art and future research directions. International Journal of Production Research, 57(7), 2179-2202. Cavalcante, I. M., Frazzon, E. M., Forcellini, F. A., & Ivanov, D. (2019). A supervised machine learning approach to data-driven simulation of resilient supplier selection in digital manufacturing. International Journal of Information Management, 49, 86-97. Dubey, R., Gunasekaran, A., Childe, S. J., Papadopoulos, T., Blome, C., & Luo, Z. (2019). Antecedents of resilient supply chains: An empirical study. IEEE Transactions on Engineering Management, 66(1), 8-19. Hosseini, S., Ivanov, D., & Dolgui, A. (2019). Review of quantitative methods for supply chain resilience analysis. Transportation Research Part E, 125, 285-307. Hosseini, S., & Khaled, A. A. (2019). A hybrid ensemble and AHP approach for resilient supplier selection. Journal of Intelligent Manufacturing, 30(1), 207-228. Ivanov, D., Dolgui, A., & Sokolov, B. (2019). The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics. International Journal of Production Research, 57(3), 829-846. Saberi, S., Kouhizadeh, M., Sarkis, J., & Shen, L. (2019). Blockchain technology and its relationships to sustainable supply chain management. International Journal of Production Research, 57(7), 2117-2135. Ben-Daya, M., Hassini, E., & Bahroun, Z. (2019). Internet of things and supply chain management: A literature review. International Journal of Production Research, 57(15-16), 4719-4742. Brintrup, A., Pak, J., Ratiney, D., Pearce, T., Wichmann, P., Woodall, P., & McFarlane, D. (2020). Supply chain data analytics for predicting supplier disruptions: A case study in complex asset manufacturing. International Journal of Production Research, 58(11), 3330-3341. Bier, T., Lange, A., & Glock, C. H. (2020). Methods for mitigating disruptions in complex supply chain structures: A systematic literature review. International Journal of Production Research, 58(6), 1835-1856. Hosseini, S., & Ivanov, D. (2020). Bayesian networks for supply chain risk, resilience and ripple effect analysis: A literature review. Expert Systems with Applications, 161, 113649. Ivanov, D. (2020). Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak case. Transportation Research Part E, 136, 101922. Ivanov, D., & Dolgui, A. (2020). Viability of intertwined supply networks: Extending the supply chain resilience angles towards survivability. International Journal of Production Research, 58(10), 2904-2915. Kinra, A., Ivanov, D., Das, A., & Dolgui, A. (2020). Ripple effect quantification by supplier risk exposure assessment. International Journal of Production Research, 58(18), 5559-5578. Pournader, M., Kach, A., & Talluri, S. (2020). A review of the existing and emerging topics in the supply chain risk management literature. Decision Sciences, 51(4), 867-919. Queiroz, M. M., Telles, R., & Bonilla, S. H. (2020). Blockchain and supply chain management integration: A systematic review of the literature. Supply Chain Management: An International Journal, 25(2), 241-254. Ralston, P., & Blackhurst, J. (2020). Industry 4.0 and resilience in the supply chain: A driver of capability enhancement or capability loss? International Journal of Production Research, 58(16), 5006-5019. Aldrighetti, R., Battini, D., Ivanov, D., & Zennaro, I. (2021). Costs of resilience and disruptions in supply chain network design models: A review and future research directions. International Journal of Production Economics, 235, 108103. Belhadi, A., Kamble, S., Jabbour, C. J. C., Gunasekaran, A., Ndubisi, N. O., & Venkatesh, M. (2021). Manufacturing and service supply chain resilience to the COVID-19 outbreak: Lessons learned from the automobile and airline industries. Technological Forecasting and Social Change, 163, 120447. Ivanov, D., & Dolgui, A. (2021). A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0. Production Planning & Control, 32(9), 775-788. Kaur, H., & Singh, S. P. (2021). Multi-stage hybrid model for supplier selection and order allocation considering disruption risks and disruptive technologies. International Journal of Production Economics, 231, 107830. Spieske, A., & Birkel, H. (2021). Improving supply chain resilience through industry 4.0: A systematic literature review under the impressions of the COVID-19 pandemic. Computers & Industrial Engineering, 158, 107452. Wieland, A., & Durach, C. F. (2021). Two perspectives on supply chain resilience. Journal of Business Logistics, 42(3), 315-322. Dohale, V., Ambilkar, P., Gunasekaran, A., & Verma, P. (2022). Supply chain risk mitigation strategies during COVID-19: Exploratory cases of sustainable firms. International Journal of Operations & Production Management, 42(8), 1290-1318. Ozdemir, D., Sharma, M., Dhir, A., & Daim, T. (2022). Supply chain resilience during the COVID- 19 pandemic. Technology in Society, 68, 101847. Keywords predictive analytics; supplier disruption; sourcing portfolio; total cost of ownership; disruption recovery; ripple effect; resilience capability; supply risk modeling.
More Articles from INTERNATIONAL JOURNAL OF SOCIAL SCIENCES AND MANAGEMENT RESEARCH
Building National Analytics Capacity: Advances and Future Pathways
Author: Uchechi Mary-Linda Unamma, Ifeanyichukwu Jeffrey Okwesa, Uzoamaka Iwuanyanwu
Root-Cause and Thematic Analysis for Major Incident Management: A Review
Author: Ifeanyichukwu Jeffrey Okwesa, Uchechi Mary-Linda Unamma, Uzoamaka Iwuanyanwu
Data-Quality and Single-Source-Of-Truth Frameworks for Inter- Agency Reporting: A Review
Author: Uchechi Mary-Linda Unamma, Ifeanyichukwu Jeffrey Okwesa, Uzoamaka Iwuanyanwu
Human-In-The-Loop Decision Systems: Advances and Future Directions
Author: Funmilayo Ashore-Onisemo, Uchechi Mary-Linda Unamma, Ifeanyichukwu Jeffrey, Okwesa,
Roles of Oil Subsidy Removal on Transportation Cost and Water Factory in Cross River South, Nigeria
Author: Onwuzurike Peter Tobechi, Owoh Akwa Owoh, Unoh Grace Inyang, Umaru Musa